Causation Quiz

What is causation?

• Causation is the same as correlation.

• Causation is the result of random chance.

• Causation is the relationship between two unrelated events.

• Causation is the relationship between cause and effect.

What is the difference between correlation and causation?

• Correlation measures the relationship between variables, while causation refers to cause-and-effect relationship.

• Correlation is a statistical measure, while causation is a qualitative measure.

• Correlation is used to determine the cause of an effect, while causation is used to determine the strength of a relationship.

• Correlation measures the strength of a relationship, while causation measures the direction of the relationship.

Give an example of a causal relationship.

• Rain causes the ground to get wet.

• Eating causes feeling full.

• Exercise causes increased heart rate.

• Wind causes leaves to fall.

Explain the concept of a dependent variable in causation.

• The dependent variable is the variable that remains constant throughout the experiment.

• The dependent variable is the variable that causes the independent variable.

• The dependent variable is the variable being studied and measured to determine the effect or outcome of the independent variable.

• The dependent variable is the variable that is manipulated by the researcher.

What is a confounding variable and how does it affect causation?

• A confounding variable is a variable that only affects the dependent variable.

• A confounding variable is an extraneous variable that can introduce a spurious relationship between the independent and dependent variables, making it difficult to determine the true cause-effect relationship.

• A confounding variable is a variable that strengthens the causation relationship.

• A confounding variable is a variable that has no effect on causation.

What is the purpose of conducting experiments in causation studies?

• To establish cause-and-effect relationships between variables.

• To test hypotheses and theories.

• To collect data for statistical analysis.

• To observe correlations between variables.

What are the limitations of establishing causation through observational studies?

• Observational studies lack control over variables and cannot establish causation.

• Observational studies are prone to selection bias and confounding variables.

• Observational studies are time-consuming and expensive.

• Observational studies rely on self-reported data which may be inaccurate.

Explain the concept of reverse causation.

• Reverse causation is when the cause and effect occur simultaneously.

• Reverse causation is when the cause is mistaken as the effect.

• Reverse causation is when there is no cause and effect relationship.

• Reverse causation is when the effect is mistaken as the cause.

What is the role of statistical analysis in determining causation?

• Statistical analysis is not useful in determining causation.

• Statistical analysis can only determine correlation, not causation.

• Statistical analysis is too complex to determine causation accurately.

• Statistical analysis helps in determining causation by examining the relationship between variables and identifying patterns or trends.

Discuss the importance of establishing causation in scientific research.

• To determine cause-and-effect relationships and understand underlying mechanisms.

• To establish correlations between variables.

• To gather more data and increase sample size.

• To make predictions about future outcomes.